This paper proposes a, namely, asynchronous chain and presents a Variable Bulk Arrival and Asynchronous Bulk Service (VBAABS) model of the type in order to provide a quantitative method to design an asynchronous chain as a basis in its initial theoretical design stage. Note that the proposed chain is precisely and namely asynchronous along with adaptive-sized blocks in a proactive manner versus the conventional chain that controls the block posting in a strictly synchronous manner to the fixed-sized blocks. The model of the type (i.e., VBAVBS) is considered as the theoretical and quantitative baseline model for the proposed model, namely, an adaptive chain model, yet with a rather reactively dynamic size of blocks, while the proposed asynchronous model carries a proactively dynamic (or adaptive) size of blocks. The proposed asynchronous chain model assumes variable bulk arrivals of transactions in Poisson distribution, i.e., , where represents the number of slots across all the mined transactions, and variable asynchronous services of transactions, each of which applies to a block potentially of different capacity in terms of the number of slots in it, in exponential time, i.e., , for being posted in the current block, namely, VBAABS. The major quantitative distinction between the adaptive model, i.e., VBAVBS, and the asynchronous model, i.e., VBAABS, is that in VBAVBS, every state , where , transitions back into while in VBAABS, every state , where , transitions back into , where , as well as back into , and is the state in which the transaction up in execution is to be discarded, in other words, that the current block capacity is in excess of the required capacity for the transaction in execution to result in a potentially excessive delay as much as than an otherwise ordinarily fully synchronous block posting delay that is as much as . VBAABS will reveal the performance advantages of the asynchronous chain versus the baseline chain, i.e., VBASBS [30] and the adaptive chain, i.e., VBAVBS, with respect to the average time for a slot to wait in the block and the average spatial requirement by the slots in the block, in a quantitative manner. Extensive numerical simulations are conducted on Matlab. Further, for feasibility validation purpose, an asynchronous chain algorithm will be developed and implemented by redesigning the Ethereum open source and analyzed.
Blockchains face many challenges in time, among which the ever-growing storage needs for blockchains’ data. In particular, Ethereum is quickly approaching the 1 TB storage limit for a node, what may significantly reduce the candidates able to run an Ethereum fullnode. In this paper, we propose a new synchronization and storage strategy for Ethereum that takes full advantage of the Distributed Hash Table implemented in all clients but left unused. By digging into the history of Ethereum’s synchronization and storage strategies, we justify why such distribution of storage duties among peers makes much sense today. We implemented our solution in the official Ethereum client Geth and validated its smooth operation on a private Ethereum instance. Our solution can save around 60% of the storage of a node (360 GB) which represents a total of 12 PB of data at the network scale, while being fully backward compatible with current clients.
This paper investigates the role of the materiality of computation in two domains: blockchain technologies and artificial intelligence (AI). Although historically designed as parallel computing accelerators for image rendering and videogames, graphics processing units (GPUs) have been instrumental in the explosion of both cryptoasset mining and machine learning models. The political economy associated with video games and Bitcoin and Ethereum mining provided a staggering growth in performance and energy efficiency and this, in turn, fostered a change in the epistemological understanding of AI: from rules-based or symbolic AI towards the matrix multiplications underpinning connectionism, machine learning and neural nets. Combining a material political economy of markets with a material epistemology of science, the article shows that there is no clear-cut division between software and hardware, between instructions and tools, and between frameworks of thought and the material and economic conditions of possibility of thought itself. As the microchip shortage and the growing geopolitical relevance of the hardware and semiconductor supply chain come to the fore, the paper invites social scientists to engage more closely with the materialities and hardware architectures of 'virtual' algorithms and software.
In recent years, with the continuous promotion of blockchain technology, the application of smart contracts has shown an explosive growth trend, and smart contract vulnerabilities seriously threaten the ecological security of blockchain. Aiming at the inefficiency of existing smart contract Symbolic Execution vulnerability detection technology, this paper proposes an effective smart contract vulnerability detection method at the source code level. Firstly, we define the critical path. As attackers typically aim to steal or freeze funds, we define the path related to fund transfer as the critical path, and its related instructions are the critical instructions. Then, we constructed a smart contract control flowchart based on Ethereum bytecode and used a constraint solver to solve path constraints and corresponding vulnerability constraints. Detect common smart contract vulnerabilities such as reentrancy, access control, arithmetic vulnerabilities, unchecked low calls, and denial of service. The experimental results show that the proposed scheme has good detection performance, and vulnerability detection was performed on 55 smart contracts containing vulnerabilities in the dataset. Compared with the pre optimized scheme, the precision rate of this scheme has been improved by 7.52%, and the total execution time has been reduced by 34.92%.
The world is facing a formidable climate predicament due to elevated greenhouse gas (GHG) emissions from fossil fuels. The preceding decade has also witnessed a dramatic surge in blockchain-based applications, constituting yet another substantial energy consumer. Nonfungible tokens (NFTs) are one such application traded on Ethereum (ETH) marketplaces that have raised concerns about their climate impacts. The transition of ETH from proof of work (PoW) to proof of stake (PoS) is a step toward reducing the carbon footprint of the NFT sector. However, this alone will not address the climate impacts of the growing blockchain industry. Our analysis indicates that NFTs can cause yearly GHG emissions of up to 18% of the peak under the energy-intensive PoW algorithm. This results in a significant carbon debt of 4.56 Mt CO 2 -eq by the end of this decade, equivalent to CO 2 emissions from a 600-MW coal-fired power plant in 1 y which would meet residential power demand in North Dakota. To mitigate the climate impact, we propose technological solutions to sustainably power the NFT sector using unutilized renewable energy sources in the United States. We find that 15% utilization of curtailed solar and wind power in Texas or 50 MW of potential hydropower from existing nonpowered dams can support the exponential growth of NFT transactions. In summary, the NFT sector has the potential to generate significant GHG emissions, and measures are necessary to mitigate its climate impact. The proposed technological solutions and policy support can help promote climate-friendly development in the blockchain industry.
The gold market is currently unorganized, fragmented and suffers from various inefficiencies.Absence of regulated gold transfers may result in lack of transparency, ineffective ownership transfer, increased risk of counterfeiting, security flaws, high transaction costs, and restricted accessibility.The Ethereum blockchain gold registry aims to improve security, streamline the gold trading and ownership processes, and increase transparency by applying distributed ledger technology and smart contracts.Smart contracts facilitate automated settlement and reduce the need for manual intervention, resulting in faster and more streamlined transactions.
Marta Durá, Fátima Leal, Ángel Sánchez-García, Carlos Sáez · 7 authors
Abstract Purpose This paper analyses the feasibility of tracking data originality for pharmaceutical manufacturing in a tamper-proof manner using a geographically distributed system. The main research question is whether it is possible to ensure the traceability of drug manufacturing through the use of smart contracts and a private blockchain network. Methods This work employs a private Ethereum network with a proof-of-authority consensus algorithm to allow participating nodes to commit the medicament manufacturing originality as transactions in blocks. We use smart contracts to assess the “Original” principle of the ALCOA+ data integrity principles for full sensor-enabled production lines within pharmaceutical manufacturing plants. We have evaluated our data originality assessment approach employing a temporal series of 1300 reports generated based on real datasets from pharma production lines. Out of these reports, 300 reports have been randomly tampered with to make them “unoriginal” (i.e., falsified). Results Evaluation consistently shows that the proposed approach systematically detects all the manufacturing records whether original or not, together with any source of falsification. By randomly injecting four common data falsification types, their approach effectively detects tampering and ensures the authenticity of the data originality acquired by sensors within manufacturing lines. Conclusion The approach of using a private blockchain network with a proof-of-authority consensus algorithm and smart contracts is a feasible method to track data originality for pharmaceutical manufacturing in a tamper-proof manner. In addition, this approach effectively detects tampering and ensures the authenticity of the data originality acquired by sensors within manufacturing lines.
Property transfer is one of the use cases that involves a lot of intermediaries to put trust in the system.In the present scenario, property transactions are carried out on paper, giving rise to countless conflicts.Maintaining accurate records of land ownership and transfers is a very difficult task, made even more challenging by fraudulent or incomplete registries that can be extremely hard to trace back through history.The integrity of these records is crucial, but ensuring their accuracy is a complex undertaking.Blockchain can be utilized to overcome these predicaments faced in land dealings.The transparent nature of blockchain makes it possible to securely track the transfer of ownership from one individual to another reliably.Blockchain's immutable, auditable, and traceable features makes it a suitable solution for this use case.IPFS is a decentralized protocol and peer-to-peer network that facilitates the storage and sharing of data in a distributed file system.It's designed to enable efficient and secure sharing of files across a network of computers without relying on a central server.A solution of decentralized application or DAPP on Ethereum Blockchain is proposed through this work, which will be a one stop platform for buying, selling, or registering land.A systematic approach is used, right from the registration of the land inspector/buyer/seller to the registration of lands, making it available to sell, etc.
Tema ovog diplomskog rada je Pametni ugovori temeljeni na blokchain tehnologijama s fokusom na objašnjenje njihovog funkcioniranja i primjene. U prvom dijelu rada detaljno je objašnjen koncept blockchaina koristeći primjer Bitcoina kao prve decentralizirane digitalne valute. Analizirali smo strukturu blockchaina, njegovu decentralizaciju i sigurnost transakcija. Nadalje, poseban naglasak je stavljen na Ethereum, vodeću platformu za izgradnju decentraliziranih aplikacija i pametnih ugovora. Detaljno smo opisali rad Ethereuma, uključujući Ethereum Virtual Machine (EVM), koja je glavna u izvršavanja pametnih ugovora na Ethereumu. Pametni ugovori su programabilni ugovori koji se izvršavaju na blockchainu, a u radu smo ih detaljno objasnili. Opisali smo kako se pametni ugovori programiraju koristeći jezik Solidity te kako se njihova izvršavanja osiguravaju putem konsenzusnih mehanizama blockchaina. Uz teorijski dio, rad je sadržavao i praktični primjer pametnog ugovora dijeljenja plaća zaposlenicima. U implementaciji primjera, korišten je programski jezik pametnih ugovora Solidity i Ethereum blockchain platforma. Detaljno su objašnjeni koraci izrade pametnog ugovora, definiranje uvjeta i raspodjelu plaća. Na samom kraju smo pokazali različitu primjenu blockchain tehnologije i pametnih ugovora u svijetu gdje možemo zaključiti kako blockchain tehnologija može pružiti transparentnost, sigurnost i učinkovitost u različitim sektorima. Očekuje se da će njihova primjena i utjecaj rasti u budućnosti, pružajući nove mogućnosti i promjene u raznim industrijama.
The use of digital currency or cryptocurrencies has been common since 2018. However, its use as an investment instrument is different from the conventional currency recognized by the state, this is because a cryptocurrency appeared by a number of organizations/companies and its value does not depend on the economic condition of a country, but on the status of a company/issuer of a digital currency. Difficulty predicting liability and growth creates computational needs to determine which digital currencies are suitable for investment, so in this study, 11 digital currencies are used to try out. Experiment with AHP calculations to get the best digital currency to use as an investment tool. This calculation translates into IOT Coin against other famous digital currencies, such as Bitcoin or Ethereum.
Since the debut of cryptocurrencies, particularly Bitcoin, in 2009, cryptocurrency trading has grown in popularity among investors. Relative to other conventional asset classes, cryptocurrencies exhibit high volatility and, consequently, downside risk. While the prospects of high returns are alluring for investors and speculators, the downside risks are important to consider and model. As a result, the profitability of crypto market operations depends on the predictability of price volatility. Predictive models that can successfully explain volatility help to reduce downside risk. In this paper, we investigate the value-at-risk (VaR) forecasts using a variety of volatility models, including conditional autoregressive VaR (CAViaR) and dynamic quantile range (DQR) models, as well as GARCH-type and generalized autoregressive score (GAS) models. We apply these models to five of some of the largest market capitalization cryptocurrencies (Bitcoin, Ethereum, Ripple, Litecoin, and Steller, respectively). The forecasts are evaluated using various backtesting and model confidence set (MCS) techniques. To create the best VaR forecast model, a weighted aggregative technique is used. The findings demonstrate that the quantile-based models using a weighted average method have the best ability to anticipate the negative risks of cryptocurrencies.
The Non-Fungible Token (NFT) has experienced tremendous growth in recent years. The concept of NFT is essentially a digital asset that operates based on smart contracts on blockchain, traded with cryptocurrencies like Ethereum, Tezos, Solana, etc. Public attention towards NFT has exploded in 2021. Despite its popularity and skyrocketing trading prices, little is known about the economics, people's perception, and experiences with NFT. Therefore, this research aims to provide diverse insights into NFT, its benefits and limitations, as well as the potential of NFT and the metaverse. In this study, the researcher conducted a qualitative study involving 21 respondents, including users, gaming communities, and cryptocurrency traders in the city of Batam. This research utilized semi-structured interviews and descriptive analysis as the research methods. The findings from this research conclude that the respondents recommend harnessing NFT and can find benefits from utilizing the technology.
It is important to determine the network effects and store-of-value feature of cryptocurrencies due to the argument that it could be considered as a new ‘asset class’. Current studies on cryptocurrencies' network effects mainly focused on using Metcalfe's Law to evaluate the relationship between cryptocurrency prices and the squared number of active wallets addresses. In terms of cryptocurrencies' store-of-value features, previous studies primarily compared daily volatility of limited number of popular cryptocurrencies to Gold. Extant studies are also based on out-of-date data. This research extends the literature by using up-to-date daily data of a sample of the top 100 cryptocurrencies covering 2010–2023 to explore the network effects and the store of value characteristics of a wide range of cryptocurrencies. Firstly, we used nonlinear regression models to examine the relationship between cryptocurrency prices and active wallets addresses, the number of transactions and circulations. Secondly, to deepen our understanding of the store-of-value features of cryptocurrencies, we used a combination of GARCH models and time series analysis to explore the volatility in the daily returns of the sampled cryptocurrencies. Findings indicate that at least one of the network factors (i.e., active wallets addresses, the number of transactions, and number of circulation supply) have a significant effect on cryptocurrency prices. The study also finds that stable coins have comparable daily volatility as Gold, while only mature cryptocurrencies, such as PAXG, Bitcoin, Ethereum, BNB and LINK, demonstrate strong correlation with Gold. Bitcoin also showed a high positive time-series correlation with 24 of the 42 cryptocurrencies. Findings from this study provide important insights to investors, market analysts, regulators and other stakeholders on the marketisation and the store of value potentials of cryptocurrencies.
In March 2021, we witnessed a surge in Bitcoin price. The cause seemed to be a tweet by Elon Musk. Are other blockchains as sensitive to social media as Bitcoin? And more precisely, could Ethereum's popularity be explained using social media data? This work aims to explore the determinants of Ethereum's popularity. We use both data from Etherscan to retrieve the relevant historic Ethereum factors, and Twitter data. Our sample consists of data ranging from 2015 to 2022. We use Ordinary Least Squares to assess the relationship between these factors (Ethereum characteristics and Twitter data) and Ethereum's popularity. Our findings show that Ethereum's popularity - translated here by the number of daily new addresses - is related to the following elements: the Ether (ETH) price, the transaction fees, and the polarity of tweets related to Ethereum. The results could have multiple practical implications, for both researchers and practitioners. First of all, we believe that it will enable readers to better understand the technology Ethereum and its stake. Secondly, it will help the community to identify pointers for the anticipation or explanation of the popularity of existing or future platforms. And finally, the results could help in understanding the factors facilitating the design of future platforms.
Willian Fuentes Ribeiro, Daiane dos Santos, Alberto Besser
No decorrer dos últimos anos os criptoativos se tornaram uma nova tendência, ganhando importância no mercado financeiro global, devido, tanto à queda das taxas de juros internacionais, quanto à crescente procura pelos investidores que optam por investimento de maior risco. Dado o maior interesse nessa classe de ativos, ferramentas de apoio à decisão que auxiliem o investidor e os potenciais investidores são de extrema valia. Um dos objetivos do presente artigo é apresentar uma métrica para analisar a existência de quebras estruturais nas séries temporais de duas criptomoedas que atualmente apresentam grandes volumes de negociações (Bitcoin e Ethereum). Utilizou-se o teste de Chow para comprovar as “quebras” numa tendência estável da série histórica das duas criptomoedas. As séries temporais analisadas contemplaram o período de um ano a partir de janeiro de 2022 e suas negociações respectivamente até o mês de dezembro de 2022. Foram encontrados 7 choques em ambas as moedas, estes em períodos correlacionados, associados a fatores exógenos, principalmente fatores sanitários e econômicos como Covid-19 e guerra da Ucrânia, além de fatos impactantes no mercado cripto, como a falência da empresa FTX Trading Ltd e a instabilidades na inflação nos EUA.
Penelitian ini bertujuan untuk menganalisis pengaruh volatilitas spillover harga bitcoin terhadap harga ethereum, harga tether dan juga harga emas dunia pada periode tahun 2016-2021 menggunakan data mingguan. Penelitian ini dilakukan karena cryptocurrency memiliki peran yang besar dalam investasi, sebagai aset alternatif dalam berinvestasi dengan return yang diberikan cenderung tinggi dan juga memanfaatkan teknologi digital sehingga lebih fleksibel dalam transaksi. Di lain sisi aset yang dimiliki kripto memiliki manfaat dalam membantu proses transaksi ataupun pertukaran mata uang lain dalam bentuk dollar, rupiah ataupun mata uang lainnya.Analisis dalam penelitian ini menggunakan model exponential generalized autoregresive conditional heteroscedasticity (EGARCH) dengan teknik pengambilan sampel berupa purposive sampling. Hasil menunjukkan bahwa terdapat pengaruh volatilitas spillover antara bitcoin dengan ethereum. Selain itu, terdapat shock positive yang lebih banyak dari pada shock negative pada volatilitas harga bitcoin terhadap harga ethereum. Sedangkan untuk volatilitas spillover antara bitcoin dengan tether dan emas dunia tidak dapat dibuktikan karena data harga variabel tersebut bersifat homokedastisitas, sehingga tidak dapat dilanjutkan dengan model EGARCH karena tidak memenuhi syarat permodelan.
Liam Scholte, Rui Wang, Kwok K. Chung, Michał Aibin
Condominiums and similar properties use a stratum to manage daily operations, and owners fund it through strata fees. While existing strata fee management systems may be able to handle such funds, such systems could be more inherently transparent. It is possible to leverage the digital ledger from blockchain networks and smart contracts to build a fully transparent strata fee management system. This paper proposes designing a strata fee management system based on a smart contract in the Ethereum network. Both strata corporations and homeowners can interact with the smart contract to execute common procedures such as paying strata fees and handling expenses. Using smart contracts for strata fee management, it is believed that the chance of fraud by strata corporations is lowered compared to other systems.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Cryptocurrencies have obtained a crucial position in the international financial landscape. The cryptocurrency market has been perceived as a highly volatile market since the inception of Bitcoin. This study investigates the relevant performance of extreme value models (EVM) in estimating the Value-at-Risk (VaR) of Bitcoin and Ethereum returns. The extreme value mixture models, GPD-Normal-GPD (GNG) and GPD-KDE-GPD models are fitted to the returns of Bitcoin and Ethereum and the Kupiec likelihood backtesting procedure is performed on the VaR estimates to assess the fits. Both models’ results showed that the fits were a much more decent representation of the observed data when compared to the Normal distribution. The backtesting results showed that the GPD-KDE-GPD model’s fit was superior to that of the GPD-Normal-GPD for both sets of returns at all VaR risk levels except at the 99% level. The results of this study may assist with understanding the dynamics and risks associated with cryptocurrencies and can serve as a beneficial tool for decision-making and risk management to investors, traders, financial institutions and many other participants in the cryptocurrency ecosystem.
With the popularity of Non-Fungible Tokens (NFTs), NFTs have become a new target of phishing attacks, posing a significant threat to the NFT trading ecosystem. There has been growing anecdotal evidence that new means of NFT phishing attacks have emerged in Ethereum ecosystem. Most of the existing research focus on detecting phishing scam accounts for native cryptocurrency on the blockchain, but there is a lack of research in the area of phishing attacks of emerging NFTs. Although a few studies have recently started to focus on the analysis and detection of NFT phishing attacks, NFT phishing attack means are diverse and little has been done to understand these various types of NFT phishing attacks. To the best of our knowledge, we are the first to conduct case retrospective analysis and measurement study of real-world historical NFT phishing attacks on Ethereum. By manually analyzing the existing scams reported by Chainabuse, we classify NFT phishing attacks into four patterns. For each pattern, we further investigate the tricks and working principles of them. Based on 469 NFT phishing accounts collected up until October 2022 from multiple channels, we perform a measurement study of on-chain transaction data crawled from Etherscan to characterizing NFT phishing scams by analyzing the modus operandi and preferences of NFT phishing scammers, as well as economic impacts and whereabouts of stolen NFTs. We classify NFT phishing transactions into one of the four patterns by log parsing and transaction record parsing. We find these phishing accounts stole 19,514 NFTs for a total profit of 8,858.431 ETH (around 18.57 million dollars). We also observe that scammers remain highly active in the last two years and favor certain categories and series of NFTs, accompanied with signs of gang theft.
Abstract We examine the fractal volatility and long‐range dependence of Bitcoin, Ethereum, Tether and USD Coin by employing the continuous wavelet transform, maximal overlap discrete wavelet transform and rescaled range. Our dataset consists of daily prices spanning from January 2017 through to October 2022, encapsulating pre‐ and post‐epidemic eras. Generally, our findings suggest that Tether presents the least overall volatility throughout the time‐frequency spectrum. USD Coin demonstrates ephemeral turbulence, contrary to Tether's maturity in influencing market equilibrium through token issuance and trade responses. In the post‐epidemic sample, both stablecoins indicate mean reversion, with USD Coin showing marginally better efficiency. Conversely, investment tokens display persistent clusters due to retail traders and long‐term fundamental institutions. Although both tokens illustrate multifractal volatility, Ethereum unveils more essence of self‐similarity than Bitcoin. Hence, there is no evidence that Ethereum truly duplicates Bitcoin since policy‐related events differ between them, as both return series move incongruously. Conditional dynamics signify that all cryptocurrencies, except Tether, were affected by the pandemic transition of COVID‐19 and subsequent macroeconomic news. The unconditional volatility of stablecoins evinces zero‐mean errors, antithetical to investment tokens exhibiting annual cycles. The fractal geometry suggests that investment tokens simulate one‐dimensional lines, whereas stablecoins mimic two‐dimensional planes.
The increasing use of artificial intelligence algorithms, smart contracts, the internet of things, cryptocurrencies, and digital money highlights the need for secure and sustainable decentralized solutions. Currently, the blockchain technology serves as the backbone for most decentralized systems. However, the question of axiomatization of the blockchain theory in the first-order logic has been open until today, despite the efficient computational implementations of these systems. This did not allow one to formalize the blockchain structure, as well as to model and verify it using logical methods. This work introduces a finitely axiomatizable blockchain theory T that defines a class of blockchain structures K using the axioms of the first-order logic. The models of the theory T are well-known blockchain implementations with the proof of work consensus algorithm, including Bitcoin, Ethereum (PoW version), Ethereum Classic, and some others. By utilizing mathematical logic, we can study these models and derive new theorems of the theory T through automatic proofs. Also, the axiomatization of blockchain opens up new opportunities to develop blockchain-based systems that can help solve some of the open problems in the fields of artificial intelligence, robotics, cryptocurrencies, etc.
Smart contracts play a vital role in the Ethereum ecosystem. Due to the prevalence of kinds of security issues in smart contracts, the smart contract verification is urgently needed, which is the process of matching a smart contract's source code to its on-chain bytecode for gaining mutual trust between smart contract developers and users. Although smart contract verification services are embedded in both popular Ethereum browsers (e.g., Etherscan and Blockscout) and official platforms (i.e., Sourcify), and gain great popularity in the ecosystem, their security and trustworthiness remain unclear. To fill the void, we present the first comprehensive security analysis of smart contract verification services in the wild. By diving into the detailed workflow of existing verifiers, we have summarized the key security properties that should be met, and observed eight types of vulnerabilities that can break the verification. Further, we propose a series of detection and exploitation methods to reveal the presence of vulnerabilities in the most popular services, and uncover 19 exploitable vulnerabilities in total. All the studied smart contract verification services can be abused to help spread malicious smart contracts, and we have already observed the presence of using this kind of tricks for scamming by attackers. It is hence urgent for our community to take actions to detect and mitigate security issues related to smart contract verification, a key component of the Ethereum smart contract ecosystem.
Engineering systems have been designed to facilitate society. These systems can be seen everywhere in our daily lives ranging from electrical systems to mechanical systems, and from bio-medical systems to industrial systems. With tight coupling with information and communication technology (ICT), these engineering systems can be even controlled and monitored remotely. These systems are supported massively with sensors through which they capture enormous data, which are then used to improve the performance of the systems. Moreover, complex processes are involved in the overall functioning of these engineering systems. The management of data and processes within these engineering systems has been done through traditional ways such as database management systems or spread sheets; however, involvement of multiple parties makes these engineering systems more complex to operate, track, and audit. Blockchain technology has the potential to replace traditional database systems and offer a level of trust in an untrusted environment. Satoshi Nakamoto is recognized as the father of blockchain technology when he first introduced Bitcoin Cryptocurrency and used this blockchain technology to store the transactions related to Bitcoin. Among thousands of cryptocurrencies in the market, Bitcoin is still one of the largest cryptocurrencies in the market in terms of market capital. However, cryptocurrencies are not the only use-case where blockchain technology has been used. There are many other application areas where blockchain technology has been used such as education, telecommunication, health, government, logistics, and asset management, just to name a few. With features of immutability, traceability, transparency, availability, and decentralization, blockchain technology is a good match for engineering systems. Blockchain technology can help in the supply chain of these engineering systems, as well as facilitate data, process, and parties. Considering enormous applications of blockchain technology in engineering systems, Engineering Reports ran this Special Section and invited original scientific and technical contributions. In this Special Section, we received nine submissions, of which, after rigorous peer-review process, three high-quality papers were accepted. In the first paper entitled “Machine-as-a-Service: Blockchain-based management and maintenance of industrial appliances” by Viet Hoang Tran et al., the authors considered an industrial setting where an emerging service model, that is, Machine-as-a-Service, has been introduced, in which industrial machines are rented and then tracked through blockchain-based system. In the proposed system, authors suggested to use Ethereum, and Inter Planetary File System (IFPS) and a reference architecture was also proposed. Both experiments on Microsoft Azure Cloud platform and network emulation over Enoslib were conducted to show the performance of the proposed architecture. The second paper entitled “SENSIBLE: SEquestered aNd SynergIstic BLockchain Ecosystem” by Meghana Kshirsagar et al.; the authors proposed a personalized patient healthcare framework using blockchain technology. Using the open-source synthetic patient dataset generator Synthea, the proposed framework was evaluated on Ethereum to show the effectiveness of secured data access in this setting. The third and last paper, entitled “A blockchain-enabled solution to improve intra-inter organizational innovation processes in software small medium enterprises” by Chetna Gupta et al., considered blockchain technology to manage security, knowledge sharing, and information management of software small medium enterprises (SSMEs). In the end, we would like to thank the authors who submitted their works to this Special Section and to the reviewers, who provided their in-depth reviews, which ultimately helped the authors enhance the quality of their work. The Guest Editor is also thankful to the Managing Editor and Editorial Office Staff of Engineering Reports for their guidance and help during the whole process of this Special Section. We hope you enjoy reading this Special Section. Mubashir Husain Rehmani: Conceptualization (lead); project administration (lead); writing – original draft (lead); writing – review and editing (lead). Authors have no conflict of interest relevant to this article. The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer-review/10.1002/eng2.12727. Mubashir Husain Rehmani (M'14-SM'15, SFHEA) received the B.Eng. degree in computer systems engineering from Mehran University of Engineering and Technology, Jamshoro, Pakistan, in 2004, the M.S. degree from the University of Paris XI, Paris, France, in 2008, and the Ph.D. degree from the University Pierre and Marie Curie, Paris, in 2011. He is currently working as Lecturer in the Department of Computer Science, Munster Technological University (MTU), Ireland. Prior to this, he worked as Post-Doctoral Researcher at the Telecommunications Software and Systems Group (TSSG), Waterford Institute of Technology (WIT), Waterford, Ireland. He also served for 5 years as an Assistant Professor at COMSATS Institute of Information Technology, Wah Cantt., Pakistan. He is serving as an Editorial Board Member of NATURE Scientific Reports. He is currently an Area Editor of the IEEE Communications Surveys and Tutorials and IEEE Open Journal of Communications Society. He is serving as an Associate Editor for Engineering Reports. He served for 3 years (from 2015 to 2017) as an Associate Editor of the IEEE Communications Surveys and Tutorials. He served as Column Editor for Book Reviews in IEEE Communications Magazine. He is appointed as Associate Editor for IEEE Transactions on Green Communication and Networking and IEEE Transactions on Cognitive Communications and Networking. Currently, he serves as Associate Editor of Elsevier Journal of Network and Computer Applications (JNCA), and the Journal of Communications and Networks (JCN). He is also serving as a Guest Editor of Elsevier Ad Hoc Networks journal, Elsevier Future Generation Computer Systems journal, the IEEE Transactions on Industrial Informatics, and Elsevier Pervasive and Mobile Computing journal. He has authored/edited total eight books. Two books with Springer, two books published by IGI Global, USA, three books published by CRC Press—Taylor and Francis Group, UK, and one book with Wiley, UK. He received “Best Researcher of the Year 2015 of COMSATS Wah” award in 2015. He received the certificate of appreciation, “Exemplary Editor of the IEEE Communications Surveys and Tutorials for the year 2015” from the IEEE Communications Society. He received Best Paper Award from IEEE ComSoc Technical Committee on Communications Systems Integration and Modeling (CSIM), in IEEE ICC 2017. He consecutively received research productivity award in 2016–2017 and also ranked 1 in all Engineering disciplines from Pakistan Council for Science and Technology (PCST), Government of Pakistan. He received Best Paper Award in 2017 from Higher Education Commission (HEC), Government of Pakistan. He is the recipient of Best Paper Award in 2018 from Elsevier Journal of Network and Computer Applications. He is the recipient of Highly Cited Researcher™ award thrice in 2020, 2021, and 2022 by Clarivate, USA. His performance in this context features in the TOP 1% by citations in the field of Computer Science and Cross Field in the Web of Science™ citation index. He is the only researcher from Ireland in the field of “Computer Science” who received this International prestigious award. In October 2022, he received Science Foundation Ireland's CONNECT Centre's Education and Public Engagement (EPE) Award 2022 for his research outreach work and being a spokesperson for achieving a work–life balance for a career in research.